Discovery and Characterization of a New Kind of Translational Enhancer 3'UTRs of cellular and viral mRNAs harbor elements that function in gene expression by enhancing translation using unknown mechanisms. To determine the function of these elements we used a simple model, the Turnip crinkle virus (TCV). TCV is translated in a cap-independent fashion and contains a 3'region that together with the 5'UTR synergistically enhances translation. We used MPGAfold and Structurelab to identify a series of hairpins and two pseudoknots that were confirmed genetically. Using this structural information with our 3D molecular modeling software, we predicted a structure that resembled a tRNA, the first internal tRNA-like structure found in nature. We then proposed that translational enhancement by the element might involve ribosome binding. The element was found to bind the 60S ribosomal subunit, the first such interaction with the large subunit discovered. It was biochemically determined that this tRNA-like element is a major part of a switch that converts the template from one that is translated to one that is replicated. We further investigated the formation of this unique translational enhancer utilizing a newly developed technique that combines Small Angle X-ray Scattering (SAXS) and Residual Dipolar Coupling (RDC) (see below). The results verified the basic model that had been predicted computationally and proved the efficacy of the technique for large RNAs, in addition to further characterizing this newly discovered translational enhancer element. This may open the door to the discovery of similar mechanisms in other genes. Characteristics that Determine Abundance of Two-Thirds of Proteins in a Human Cell Line Transcription, mRNA decay, translation, and protein degradation all contribute to steady state protein concentrations in multi-cellular eukaryotes. In this research, experimental measurements and computational studies were done to determine the absolute protein and mRNA abundances in cellular lysates from the human Daoy medulloblastoma cell line, and the properties that contributed to these abundances. Sequence features related to translation and protein degradation explained two-thirds of protein abundance variation. mRNA sequence lengths, amino acid properties, upstream open reading frames and secondary structures in the 5'untranslated region (UTR) showed the strongest individual correlations for protein concentrations. In a combined model, characteristics of the coding region and the 3'UTR explained a larger proportion of protein abundance variation than characteristics of the 5'UTR. Cis Acting Elements in the 3'UTR of Dengue Virus Over 50 million case of dengue fever are reported each year with 10% of these leading to severe forms of the disease. Using MPGAfold (our massively parallel genetic algorithm for RNA folding) we showed that the core region of the 3'untranslated region of dengue virus RNA can form two dumbell structures of unequal frequencies of occurence. It was experimentally shown that structural motifs formed from these dumbells are important for viral replication. In addition, it was shown that there is a cooperative synergy with both dumbells for translation. Thus, we showed that the cis-acting elements in the core region of dengue virus are require for both replication and optimal translation. Correlating SHAPE Signatures with 3D RNA Structures Selective 2-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) is a relatively easy technique for the quantitative analysis of RNA secondary structure. In general, low SHAPE signal values are correlated with Watson-Crick base pairing, and high values indicate positions that are single-stranded within the RNA structure. The relationship of the measured SHAPE signal to structural properties such as non-Watson-Crick base pairing or the position of a nucleotide within an RNA double helix has thus far not been thoroughly investigated. In this research we presented results of SHAPE experiments performed on a set of seven RNAs with published 3D structures. We found that the RNA SHAPE signal depends on the type of base pairs a nucleotide is involved in;also we found a strong correlation between the SHAPE signal corresponding to a nucleotide and its position in an RNA double helix. Data Mining of Functional RNA Structures in Genomic Sequences The normal functions of genomes depend on the precise expression of messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs), such as microRNAs. These ncRNAs and functional RNA structures (FRSs) act as regulators or response elements for cellular factors, participate in transcription, post-transcriptional processing, and translation. In RNA-based regulation, the regulatory RNAs are often correlated with distinct higher-order structures. Computational simulations have indicated that a large number of FRSs are both significantly more structured and thermodynamically more stable. Various computational tools have been developed and the structural features of ncRNAs and FRSs have been determined. In this study we discuss our efforts in the computational discovery of structured features of ncRNAs and FRSs within complex genomes. Characterizing Structural Features for Small Regulatory RNAs in E. Coli Small regulatory RNAs are highly abundant noncoding RNAs (ncRNA) found in bacterial genomes. These small regulatory ncRNAs (sRNAs) can regulate the synthesis of proteins by mediating mRNA transcription, translation and stability. Furthermore, they also control the activity of specific proteins by binding to them. In this research, we describe a general computational approach for identifying the distinct structure of sRNAs in the Escherichia coli (E. coli) genomes by a quantitative measure that is the energy difference between the optimal structure folded from a sequence segment and its corresponding optimal restrained structure where all base pairings formed in the original optimal structure are excluded. Our results indicated that most of the known small ncRNAs in E. coli K12 have very high normalized scores with high statistical significance. These sRNAs have distinct well-ordered structures that are both thermodynamically stable and uniquely folded. CyloFold CyloFold is a new algorithm accessible via our webserver that predicts RNA secondary structure with pseudoknots. Pseudoknot prediction is unrestricted, thus permitting the formation of a multitude of pseudoknots with high degrees of complexity. A unique aspect of the algorithm is a coarse-grained mechanism that checks for steric feasibility of the chosen set of helices representing the structure. Helicical combinations that produce steric conflicts are eliminated from consideration in the predicted structure.